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相关论文: Dynamical Behaviors of the Tumor-immune System in …

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We propose a mathematical kinetic framework to investigate interactions between tumor cells and the immune system, focusing on the spatial dynamics of tumor progression and immune responses. We develop two kinetic models: one describes a…

细胞行为 · 定量生物学 2026-02-24 Martina Conte , Romina Travaglini

Tumor-immune interactions are shaped by both antigenic heterogeneity and stochastic perturbations in the tumor microenvironment, yet the mathematical mechanisms underlying immune phase transitions remain poorly understood. We propose a…

种群与进化 · 定量生物学 2025-09-16 Mengfan Tan , Shaoqing Chen , Chunjin Wei , Da Zhou

Tumor-immune interactions are central to cancer progression and treatment outcomes. In this study, we present a stochastic agent-based model that integrates cellular heterogeneity, spatial cell-cell interactions, and drug resistance…

组织与器官 · 定量生物学 2026-05-19 Yuhong Zhang , Chenghang Li , Boya Wang , Jinzhi Lei

We propose an extension of a standard stochastic individual-based model in population dynamics which broadens the range of biological applications. Our primary motivation is modelling of immunotherapy of malignant tumours. In this context…

种群与进化 · 定量生物学 2016-04-18 Martina Baar , Loren Coquille , Hannah Mayer , Michael Hölzel , Meri Rogava , Thomas Tüting , Anton Bovier

In the paper we investigate a mathematical model describing the growth of tumor in the presence of immune response of a host organism. The dynamics of tumor and immune cells is based on the generic Michaelis-Menten kinetics depicting…

Spatial interactions between cancer and immune cells, as well as the recognition of tumour antigens by cells of the immune system, play a key role in the immune response against solid tumours. The existing mathematical models generally…

细胞行为 · 定量生物学 2019-08-05 Fiona R Macfarlane , Mark AJ Chaplain , Tommaso Lorenzi

In this paper we investigate some stochastic models for tumor-immune systems. To describe these models we used a Wiener process, as the noise has a stabilization effect. Their dynamics are studied in terms of stochastic stability in the…

动力系统 · 数学 2009-06-17 O. Chis , D. Opris

The interactions between tumor cells and the immune system play a crucial role in cancer evolution. In this study, we explore how these interactions influence cancer progression by modeling the relationships among naive T cells, effector T…

组织与器官 · 定量生物学 2025-03-19 Haifeng Zhang , Changjing Zhuge , Jinzhi Lei

We study the joint effect of thermal bath fluctuations and an external noise tuning activity of cytotoxic cells on the triggered immune response in a growing cancerous tissue. The immune response is assumed to be primarily mediated by…

种群与进化 · 定量生物学 2015-06-26 Anna Ochab-Marcinek , Ewa Gudowska-Nowak

We present a model for the interaction dynamics of lymphocytes-tumor cells population. This model reproduces all known states for the tumor. Futherly,we develop it taking into account periodical immunotheraphy treatment with cytokines…

In this paper we investigate some stochastic models for tumor-immune systems. To describe these models, we used a Wiener process, as the noise has a stabilization effect. Their dynamics are studied in terms of stochastic stability in the…

动力系统 · 数学 2009-09-09 O. Chis , A. Sandru , D. Opris

The influence of random fluctuations on the recruitment of effector cells towards a tumor is studied by means of a stochastic mathematical model. Aggressively growing tumors are confronted against varying intensities of the cell-mediated…

其他定量生物学 · 定量生物学 2020-10-28 Irina Bashkirtseva , Lev Ryashko , Álvaro G. López , Jesus M. Seoane , Miguel A. F. Sanjuán

A spatiotemporal noise is assumed to reflect the environmental fluctuation in a spatially extended tumor system. We introduce firstly the structure factor to reveal the invasive tumor growth quantitatively. The homogenous environment can…

其他定量生物学 · 定量生物学 2009-11-13 Wei-Rong Zhong , Yuan-Zhi Shao , Li Li , Feng-Hua Wang , Zhen-Hui He

We consider a three-state model comprising tumor cells, effector cells and tumor detecting cells under the influence of noises. It is demonstrated that inevitable stochastic forces existing in all three cell species are able to suppress…

组织与器官 · 定量生物学 2011-07-05 Thomas Bose , Steffen Trimper

The stochastic discrete space-time model of an immune response on tumor spreading in a two-dimensional square lattice has been developed. The immunity-tumor interactions are described at the cellular level and then transferred into the…

comp-gas · 物理学 2007-05-23 Margarita Voitikova

Although the immune response is often regarded as acting to suppress tumor growth, it is now clear that it can be both stimulatory and inhibitory. The interplay between these competing influences has complex implications for tumor…

细胞行为 · 定量生物学 2013-05-17 Kathleen P. Wilkie , Philip Hahnfeldt

We investigate noise-induced pattern formation in a model of cancer growth based on Michaelis-Menten kinetics, subject to additive and multiplicative noises. We analyse stability properties of the system and discuss the role of diffusion…

细胞行为 · 定量生物学 2007-05-23 Anna Ochab-Marcinek

We formulate the dynamical model for the anti-tumor immune response based on intercellular cytokine-mediated interactions with the interleukin-2 (IL-2) taken into account. The analysis shows that the expression level of tumor antigens on…

细胞行为 · 定量生物学 2008-07-26 O. G. Isaeva , V. A. Osipov

We investigate a stochastic version of a simple enzymatic reaction which follows the generic Michaelis-Menten kinetics. At sufficiently high concentrations of reacting species, the molecular fluctuations can be approximated as a realization…

种群与进化 · 定量生物学 2009-11-13 A. Fiasconaro , A. Ochab-Marcinek , B. Spagnolo , E. Gudowska-Nowak

Among various possible causes of autoimmune disease, an important role is played by infections that can result in a breakdown of immune tolerance, primarily through the mechanism of "molecular mimicry". In this paper we propose and analyse…

组织与器官 · 定量生物学 2018-05-21 F. Fatehi , S. N. Kyrychko , A. Ross , Y. N. Kyrychko , K. B. Blyuss
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